APPLICATION OF SSR MARKERS FOR ASSESSMENT OF GENETIC SIMILARITY AND GENOTYPE IDENTIFICATION IN LOCAL WINTER WHEAT BREEDING PROGRAM
DOI: http://dx.doi.org/10.30970/sbi.1801.762
Abstract
Background. Simple sequence repeat (SSR) markers are widely used for genetic analysis in plant breeding, allowing for the investigation of genetic divergence and similarity of genotypes, identification of unique alleles and determination of levels of genetic diversity.
Materials and Methods. Analysis of 42 wheat cultivars and lines from the breeding program of Poltava State Agrarian University was carried out using 11 SSR markers located on different chromosomes. A set of 11 microsatellite single locus primer pairs was used in this study (Xgwm 11, Xgwm 44, Xgwm 46, Xgwm 135, Xgwm 174, Xgwm 186, Xgwm 194, Xgwm 219, Xgwm 312, Xgwm 372, Xgwm 389). Amplification of 11 loci was performed using the Kapa2G FastHotStart PCR Kit (Kapa Biosystems, Boston, USA). The mixture for PCR amplification contained 1.5 x Kapa2G buffer, 0.5 mM dNTP mix, 0.5 μM of each primer (Sigma-Aldrich), 1 unit of Kapa2G FastHotStart DNA Polymerase and 11.8 ng of template DNA in a volume of 25 μl. Fragment lengths were determined using GeneMapper 4.0 software (Applied Biosystems). Dendrogram was constructed using UPGMA (unweighted pair-group method with arithmetic average) in DarWin 6.0 software (Perrier and Jacquemoud-Collet 2006) for clustering analysis.
Results and Discussion. The number of alleles detected per locus varied from 5 (Xgwm 11, Xgwm 135, Xgwm 219) to 12 (Xgwm 174). A total of 80 alleles were identified for the 11 loci studied. Among these, 25 unique alleles were found, each of which was present in only one genotype. The polimorphism information content (PIC) values ranged from 0.48 to 0.87. The markers Xgwm 174 (PIC = 0.87), Xgwm 389 (PIC = 0.84) and Xgwm 372 (PIC = 0.83) were the most polymorphic in our study. We obtained a distribution of cultivars and lines by genetic similarity into five clusters.
Conclusion. The use of SSR markers made it possible to identify rare alleles within the varieties presented. The study of the genetic similarity of the presented genotypes showed their relationship according to their origin. It was shown that unique alleles tended to occur in certain local breeding genotypes. This study has shown that genotypes representing the local Ukrainian breeding program often have the same allelic variants and at the same time some genotypes have unique allelic variants. The results obtained from the study of 42 winter wheat genotypes based on 11 SSR markers showed that molecular markers can be very useful in assessing genetic similarity and identifying genotypes in the local breeding program.
Keywords
alleles, polymorphic information content, clusters, Triticum aestivum L.
Full Text:
PDFReferences
| Abdur Rehman Arif, M., Arseniuk, E., & Börner, A. (2022). Genetic variability for resistance to fungal pathogens in bread wheat. Czech Journal of Genetics and Plant Breeding, 59(1), 23-32. doi:10.17221/55/2022-cjgpb Crossref ● Google Scholar | ||||
| ||||
| Anderson, J. A., Churchill, G. A., Autrique, J. E., Tanksley, S. D., & Sorrells, M. E. (1993). Optimizing parental selection for genetic linkage maps. Genome, 36(1), 181-186. doi:10.1139/g93-024 Crossref ● PubMed ● Google Scholar | ||||
| Bányai, J., Szűcs, P., Karsai, I., Mészáros, K., Kuti, Cs., Láng, L., & Bedő, Z. (2006). Cultivar identification by molecular markers. Cereal Research Communications, 34(2-3), 865-870. doi:10.1556/crc.34.2006.2-3.213 Crossref ● Google Scholar | ||||
| ||||
| Błaszczyk, L., Tyrka, M., & Chełkowski, J. (2005). PstIAFLP based markers for leaf rust resistance genes in common wheat. Journal of Applied Genetics, 46(4), 357-364. PubMed ● Google Scholar | ||||
| ||||
| Bohn, M., Utz, H. F., & Melchinger, A. E. (1999). Genetic similarities among winter wheat cultivars determined on the basis of RFLPs, AFLPs, and SSRs and their use for predicting progeny variance. Crop Science, 39(1), 228-237. doi:10.2135/cropsci1999.0011183x003900010035x Crossref ● Google Scholar | ||||
| ||||
| Chebotar, G. A., Chebotar, S. V., & Motsnyy, I. I. (2016). Pleiotropic effects of gibberellin-sensitive and giberrellin-insensitive dwarfing genes in bread wheat of the southern step region of the Black Sea. Cytology and Genetics, 50(1), 20-27. doi:10.3103/s0095452716010023 Crossref ● Google Scholar | ||||
| ||||
| Christov, N. K., Tsonev, S., Dragov, R., Taneva, K., Bozhanova, V., & Todorovska, E. G. (2022). Genetic diversity and population structure of modern Bulgarian and foreign durum wheat based on microsatellite and agronomic data. Biotechnology & Biotechnological Equipment, 36(1), 637-652. doi:10.1080/13102818.2022.2116999 Crossref ● Google Scholar | ||||
| ||||
| Cobb, J. N., Biswas, P. S., & Platten, J. D. (2019). Back to the future: revisiting MAS as a tool for modern plant breeding. Theoretical and Applied Genetics, 132(3), 647-667. doi:10.1007/s00122-018-3266-4 Crossref ● PubMed ● PMC ● Google Scholar | ||||
| ||||
| Dobrova, H. O., Zambriborsh, І. S., & Shestopal, О. L. (2014). Methodological aspects of obtaining of durum wheat double haploids by wide hybridization. Studia Biologica, 8(3-4), 127-136. doi:10.30970/sbi.0803.380 (In Ukrainian) Crossref ● Google Scholar | ||||
| ||||
| Greveniotis, V., Zotis, S., Sioki, E., & Ipsilandis, C. (2020). A breeding concept to improve the performance of locally cultivated bread wheat (Triticum aestivum L.) cultivars. Czech Journal of Genetics and Plant Breeding, 56(1), 1-8. doi:10.17221/47/2019-cjgpb Crossref ● Google Scholar | ||||
| ||||
| Guo, J., Hao, C., Zhang, Y., Zhang, B., Cheng, X., Qin, L., Li, T., Shi, W., Chang, X., Jing, R., Yang, W., Hu, W., Zhang, X., & Cheng, S. (2015). Association and validation of yield-favored alleles in chinese cultivars of common wheat (Triticum aestivum L.). PLoS One, 10(6), e0130029. doi:10.1371/journal.pone.0130029 Crossref ● PubMed ● PMC ● Google Scholar | ||||
| ||||
| Hickey, L. T., N. Hafeez, A., Robinson, H., Jackson, S. A., Leal-Bertioli, S. C. M., Tester, M., Gao, C., Godwin, I. D., Hayes, B. J., & Wulff, B. B. H. (2019). Breeding crops to feed 10 billion. Nature Biotechnology, 37(7), 744-754. doi:10.1038/s41587-019-0152-9 Crossref ● PubMed ● Google Scholar | ||||
| ||||
| Kong, L., Ohm, H. W., Cambron, S. E., & Williams, C. E. (2005). Molecular mapping determines that Hessian fly resistance gene H9 is located on chromosome 1A of wheat. Plant Breeding, 124(6), 525-531. doi:10.1111/j.1439-0523.2005.01139.x Crossref ● Google Scholar | ||||
| ||||
| Korzun V. (2002). Use of molecular markers in cereal breeding. Cellular & Molecular Biology Letters, 7(2B), 811-820. PubMed ● Google Scholar | ||||
| ||||
| Körmöczi, P., Tóth, B., Nagy-György, A., Kocsis, K., Óvári, J., Szabó, B. P., Véha, A., & Cseuz, L. (2020). SNP-based genetic diversity assessment among hungarian bread wheat (Triticum aestivum L.) genotypes. Cereal Research Communications, 48(1), 1-7. doi:10.1007/s42976-019-00005-z Crossref ● Google Scholar | ||||
| ||||
| Kota, S., Mohapatra, T., & Brajendra. (2014). Assessment of genetic diversity in wheat released from 1905 and breeding lines using microsatellite marker. Research Journal of Biotechnology, 9(2), 14-22. Google Scholar | ||||
| ||||
| Kuleung, C., Baenziger, P. S., Kachman, S. D., & Dweikat, I. (2006). Evaluating the genetic diversity of triticale with wheat and rye SSR markers. Crop Science, 46(4), 1692-1700. doi:10.2135/cropsci2005.09-0338 Crossref ● Google Scholar | ||||
| ||||
| Kumar, S., Kumar, V., Kumari, P., Singh, A. K., & Singh, R. (2016). DNA fingerprinting and genetic diversity studies in wheat genotypes using SSR markers. Journal of Environmental Biololy, 37(2), 319-326. Retrieved from http://jeb.co.in/journal_issues/201603_mar16/paper_20.pdf Google Scholar | ||||
| ||||
| Lagodiienko, V., Bogdanov, O., Lagodiienko, V. (2019). Place and role of Ukraine in the world wheat market. Ukrainian Journal of Applied Economics, 4(3), 297-308. doi:10.36887/2415-8453-2019-3-33 (In Ukrainian) Crossref ● Google Scholar | ||||
| ||||
| Landjeva, S., Ganeva, G., Korzun, V., Palejev, D., Chebotar, S., & Kudrjavtsev, A. (2015). Genetic diversity of old bread wheat germplasm from the Black Sea region evaluated by microsatellites and agronomic traits. Plant Genetic Resources, 13(2), 119-130. doi:10.1017/s1479262114000781 Crossref ● Google Scholar | ||||
| ||||
| Lenaerts, B., Collard, B. C. Y., & Demont, M. (2019). Review: improving global food security through accelerated plant breeding. Plant Science, 287, 110207. doi:10.1016/j.plantsci.2019.110207 Crossref ● PubMed ● PMC ● Google Scholar | ||||
| ||||
| Litvinenko, M., Lyfenko, S., Poperelya, F., Babajants, L., & Palamatchuk, A. (2001). Ukrainian wheat pool. In A. P. Bonjean, & W. J. Angus (Eds), The world wheat book: a history of wheat breeding (Vol. 1, pp. 351-375). Paris: Lavoisier Publishing. Google Scholar | ||||
| ||||
| Nei, M., & Li, W. H. (1979). Mathematical model for studying genetic variation in terms of restriction endonucleases. Proceedings of the National Academy of Sciences, 76(10), 5269-5273. doi:10.1073/pnas.76.10.5269 Crossref ● PubMed ● PMC ● Google Scholar | ||||
| ||||
| OECD/FAO (2021). OECD-FAO Agricultural Outlook 2021-2030. OECD Publishing, Paris, doi:10.1787/19428846-en Crossref ● Google Scholar | ||||
| ||||
| Oslovičová, V., Simmonds, J. R., Snape, J. W., Gálová, Z., Balážová, Z., & Matušíková, I. (2014). Molecular marker-based characterization of a set of wheat genotypes adapted to Central Europe. Cereal Research Communications, 42(2), 189-198. doi:10.1556/crc.42.2014.2.2 Crossref ● Google Scholar | ||||
| ||||
| Pandurangan, S., Workman, C., Nilsen, K., & Kumar, S. (2022). Introduction to marker-assisted selection in wheat breeding. In A. Bilichak & J. D. Laurie (Eds), Accelerated breeding of cereal crops (pp. 77-117). New York, NY: Springer US. doi:10.1007/978-1-0716-1526-3_3 Crossref ● Google Scholar | ||||
| ||||
| Rimbert, H., Darrier, B., Navarro, J., Kitt, J., Choulet, F., Leveugle, M., … Paux, E. (2018). High throughput SNP discovery and genotyping in hexaploid wheat. PLoS One, 13(1), e0186329. doi:10.1371/journal.pone.0186329 Crossref ● PubMed ● PMC ● Google Scholar | ||||
| ||||
| Röder, M. S., Korzun, V., Wendehake, K., Plaschke, J., Tixier, M.-H., Leroy, P., & Ganal, M. W. (1998). A microsatellite map of wheat. Genetics, 149(4), 2007-2023. doi:10.1093/genetics/149.4.2007 Crossref ● PubMed ● PMC ● Google Scholar | ||||
| ||||
| Roussel, V., Leisova, L., Exbrayat, F., Stehno, Z., & Balfourier, F. (2005). SSR allelic diversity changes in 480 European bread wheat varieties released from 1840 to 2000. Theoretical and Applied Genetics, 111(1), 162-170. doi:10.1007/s00122-005-2014-8 Crossref ● PubMed ● Google Scholar | ||||
| ||||
| Schuster, I., Vieira, E. S. N., Silva, G. J. da, Franco, F. de A., & Marchioro, V. S. (2009). Genetic variability in Brazilian wheat cultivars assessed by microsatellite markers. Genetics and Molecular Biology, 32(3), 557-563. doi:10.1590/s1415-47572009005000045 Crossref ● PubMed ● PMC ● Google Scholar | ||||
| ||||
| Singh, M., Shali, V., & Kumar, L. (2020). Diversity analysis of wheat genotypes using SSR molecular markers. International Journal of Current Microbiology and Applied Sciences, 9(10), 1413-1423. doi:10.20546/ijcmas.2020.910.168 Crossref | ||||
| ||||
| Somers, D. J., Isaac, P., & Edwards, K. (2004). A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.). Theoretical and Applied Genetics, 109(6), 1105-1114. doi:10.1007/s00122-004-1740-7 Crossref ● PubMed ● Google Scholar | ||||
| ||||
| Song, Q. J., Shi, J. R., Singh, S., Fickus, E. W., Costa, J. M., Lewis, J., Gill, B. S., Ward, R., & Cregan, P. B. (2005). Development and mapping of microsatellite (SSR) markers in wheat. Theoretical and Applied Genetics, 110(3), 550-560. doi:10.1007/s00122-004-1871-x Crossref ● PubMed ● Google Scholar | ||||
| ||||
| Spanoghe, M., Marique, T., Rivière, J., Lanterbecq, D., & Gadenne, M. (2015). Investigation and development of potato parentage analysis methods using multiplexed SSR fingerprinting. Potato Research, 58(1), 43-65. doi:10.1007/s11540-014-9271-3 Crossref ● Google Scholar | ||||
| ||||
| Stępień, Ł., Mohler, V., Bocianowski, J., & Koczyk, G. (2007). Assessing genetic diversity of Polish wheat (Triticum aestivum) varieties using microsatellite markers. Genetic Resources and Crop Evolution, 54(7), 1499-1506. doi:10.1007/s10722-006-9140-2 Crossref ● Google Scholar | ||||
| ||||
| Tams, S. H., Melchinger, A. E., & Bauer, E. (2005). Genetic similarity among European winter triticale elite germplasms assessed with AFLP and comparisons with SSR and pedigree data. Plant Breeding, 124(2), 154-160. doi:10.1111/j.1439-0523.2004.01047.x Crossref ● Google Scholar | ||||
| ||||
| Tishchenko, V. N., Batashova, M. E., & Shapochka, O. M. (2014). Indirect methods of selection in winter wheat breeding on basis of genetic correlations. Scientific Progress & Innovations, 3, 7-10. doi:10.31210/visnyk2014.03.01 Crossref ● Google Scholar | ||||
| ||||
| Toth, J., Pandurangan, S., Burt, A., Mitchell Fetch, J., & Kumar, S. (2019). Marker-assisted breeding of hexaploid spring wheat in the Canadian prairies. Canadian Journal of Plant Science, 99(2), 111-127. doi:10.1139/cjps-2018-0183 Crossref ● Google Scholar | ||||
| ||||
| Voss-Fels, K. P., Stahl, A., Wittkop, B., Lichthardt, C., Nagler, S., Rose, T., … Snowdon, R. J. (2019). Breeding improves wheat productivity under contrasting agrochemical input levels. Nature Plants, 5(7), 706-714. doi:10.1038/s41477-019-0445-5 Crossref ● PubMed ● Google Scholar | ||||
| ||||
| Zhai, H., Feng, Z., Li, J., Liu, X., Xiao, S., Ni, Z., & Sun, Q. (2016). QTL analysis of spike morphological traits and plant height in winter wheat (Triticum aestivum L.) using a high-density SNP and SSR-based linkage map. Frontiers in Plant Science, 7, 1617. doi:10.3389/fpls.2016.01617 Crossref ● Google Scholar | ||||
| ||||
| Zhang, L. Y., Bernard, M., Ravel, C., Balfourier, F., Leroy, P., Feuillet, C., & Sourdille, P. (2007). Wheat EST-SSRs for tracing chromosome segments from a wide range of grass species. Plant Breeding, 126(3), 251-258. doi:10.1111/j.1439-0523.2007.01293.x Crossref ● Google Scholar | ||||
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Mariia Batashova, Liudmyla Kryvoruchko, Bohdana Makaova-Melamud, Volodymyr Tyshchenko, Martin Spanoghe
This work is licensed under a Creative Commons Attribution 4.0 International License.